Fig 1.
The Delaunay triangulations of aggregation dataset.
Fig 2.
Example of Delaunay triangulation.
(a) Partitioning the dataset into multiple unit grids. (b) Interconnecting data points within the unit grids.
Fig 3.
The compared Delaunay triangulations of cutting edges.
(a) Edges of data points before pruning. (b) Edges of data points after pruning.
Fig 4.
Comparison of Delaunay triangulations after assigning data points.
(a) Unassigned data points. (b) After assigning data points.
Fig 5.
Comparison of Delaunay triangulations before and after merging clusters.
(a) Unmerged Clusters. (b) After Merging Clusters.
Table 1.
The details of experiment datasets.
Table 2.
Parameter Settings for Comparative Experiments.
Table 3.
Clustering Results of Algorithms on Synthetic Datasets.
Fig 6.
Visual Clustering Results of Algorithms on R15 Dataset.
(a) DPC-DG, (b) K-means, (c) HDBSCAN, (d) DPC, (e) DPCSA, (f) AP.
Fig 7.
Visual Clustering Results of Algorithms on Aggregation Dataset.
(a) DPC-DG, (b) K-means, (c) HDBSCAN, (d) DPC, (e) DPCSA, (f) AP.
Fig 8.
Visual Clustering Results of Algorithms on Compound Dataset.
(a) DPC-DG, (b) K-means, (c) HDBSCAN, (d) DPC, (e) DPCSA, (f) AP.
Fig 9.
Visual Clustering Results of Algorithms on Four Lines Dataset.
(a) DPC-DG, (b) K-means, (c) HDBSCAN, (d) DPC, (e) DPCSA, (f) AP.
Fig 10.
Visual Clustering Results of Algorithms on Circle Dataset.
(a) DPC-DG, (b) K-means, (c) HDBSCAN, (d) DPC, (e) DPCSA, (f) A.
Fig 11.
Visual Clustering Results of Algorithms on Smile Dataset.
(a) DPC-DG, (b) K-means, (c) HDBSCAN, (d) DPC, (e) DPCSA, (f) FCM.
Table 4.
Clustering results of real datasets.